1. The use of stable isotope data to infer characteristics of community structure and niche width of community members has become increasingly common. Although these developments have provided ...ecologists with new perspectives, their full impact has been hampered by an inability to statistically compare individual communities using descriptive metrics. 2. We solve these issues by reformulating the metrics in a Bayesian framework. This reformulation takes account of uncertainty in the sampled data and naturally incorporates error arising from the sampling process, propagating it through to the derived metrics. 3. Furthermore, we develop novel multivariate ellipse-based metrics as an alternative to the currently employed Convex Hull methods when applied to single community members. We show that unlike Convex Hulls, the ellipses are unbiased with respect to sample size, and their estimation via Bayesian inference allows robust comparison to be made among data sets comprising different sample sizes. 4. These new metrics, which we call SIBER (Stable Isotope Bayesian Ellipses in R), open up more avenues for direct comparison of isotopic niches across communities. The computational code to calculate the new metrics is implemented in the free-to-download package Stable Isotope Analysis for the R statistical environment.
Stable isotope analysis is increasingly being utilised across broad areas of ecology and biology. Key to much of this work is the use of mixing models to estimate the proportion of sources ...contributing to a mixture such as in diet estimation.
By accurately reflecting natural variation and uncertainty to generate robust probability estimates of source proportions, the application of Bayesian methods to stable isotope mixing models promises to enable researchers to address an array of new questions, and approach current questions with greater insight and honesty.
We outline a framework that builds on recently published Bayesian isotopic mixing models and present a new open source R package, SIAR. The formulation in R will allow for continued and rapid development of this core model into an all-encompassing single analysis suite for stable isotope research.
Ferroelectric absorbers, which promote carrier separation and exhibit above-gap photovoltages, are attractive candidates for constructing efficient solar cells. Using the ferroelectric insulator ...BaTiO sub(3) we show how photogeneration and the collection of hot, non-equilibrium electrons through the bulk photovoltaic effect (BPVE) yields a greater-than-unity quantum efficiency. Despite absorbing less than a tenth of the solar spectrum, the power conversion efficiency of the BPVE device under 1 sun illumination exceeds the Shockley-Queisser limit for a material of this bandgap. We present data for devices that feature a single-tip electrode contact and an array with 24 tips (total planar area of 11 mu m super(2)) capable of generating a current density of 17mAcm super(-2) under illumination of AM1.5G. In summary, the BPVE at the nanoscale provides an exciting new route for obtaining high-efficiency photovoltaic solar energy conversion.
The ongoing evolution of tracer mixing models has resulted in a confusing array of software tools that differ in terms of data inputs, model assumptions, and associated analytic products. Here we ...introduce MixSIAR, an inclusive, rich, and flexible Bayesian tracer (e.g., stable isotope) mixing model framework implemented as an open-source R package. Using MixSIAR as a foundation, we provide guidance for the implementation of mixing model analyses. We begin by outlining the practical differences between mixture data error structure formulations and relate these error structures to common mixing model study designs in ecology. Because Bayesian mixing models afford the option to specify informative priors on source proportion contributions, we outline methods for establishing prior distributions and discuss the influence of prior specification on model outputs. We also discuss the options available for source data inputs (raw data versus summary statistics) and provide guidance for combining sources. We then describe a key advantage of MixSIAR over previous mixing model software-the ability to include fixed and random effects as covariates explaining variability in mixture proportions and calculate relative support for multiple models via information criteria. We present a case study of
diet partitioning to demonstrate the power of this approach. Finally, we conclude with a discussion of limitations to mixing model applications. Through MixSIAR, we have consolidated the disparate array of mixing model tools into a single platform, diversified the set of available parameterizations, and provided developers a platform upon which to continue improving mixing model analyses in the future.
Human actions challenge nature in many ways. Ecological responses are ineluctably complex, demanding measures that describe them succinctly. Collectively, these measures encapsulate the overall ...‘stability’ of the system. Many international bodies, including the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services, broadly aspire to maintain or enhance ecological stability. Such bodies frequently use terms pertaining to stability that lack clear definition. Consequently, we cannot measure them and so they disconnect from a large body of theoretical and empirical understanding. We assess the scientific and policy literature and show that this disconnect is one consequence of an inconsistent and one‐dimensional approach that ecologists have taken to both disturbances and stability. This has led to confused communication of the nature of stability and the level of our insight into it. Disturbances and stability are multidimensional. Our understanding of them is not. We have a remarkably poor understanding of the impacts on stability of the characteristics that define many, perhaps all, of the most important elements of global change. We provide recommendations for theoreticians, empiricists and policymakers on how to better integrate the multidimensional nature of ecological stability into their research, policies and actions.
Biological invasions are a significant driver of human-induced global change and many ecosystems sustain sympatric invaders. Interactions occurring among these invaders have important implications ...for ecosystem structure and functioning, yet they are poorly understood. Here we apply newly developed metrics derived from stable isotope data to provide quantitative measures of trophic diversity within populations or species. We then use these to test the hypothesis that sympatric invaders belonging to the same functional feeding group occupy a smaller isotopic niche than their allopatric counterparts. Two introduced, globally important, benthic omnivores, Louisiana swamp crayfish (Procambarus clarkii) and carp (Cyprinus carpio), are sympatric in Lake Naivasha, Kenya. We applied our metrics to an 8-year data set encompassing the establishment of carp in the lake. We found a strong asymmetric interaction between the two invasive populations, as indicated by inverse correlations between carp abundance and measures of crayfish trophic diversity. Lack of isotopic niche overlap between carp and crayfish in the majority of years indicated a predominantly indirect interaction. We suggest that carp-induced habitat alteration reduced the diversity of crayfish prey, resulting in a reduction in the dietary niche of crayfish. Stable isotopes provide an integrated signal of diet over space and time, offering an appropriate scale for the study of population niches, but few isotope studies have retained the often insightful information revealed by variability among individuals in isotope values. Our population metrics incorporate such variation, are robust to the vagaries of sample size and are a useful additional tool to reveal subtle dietary interactions among species. Although we have demonstrated their applicability specifically using a detailed temporal dataset of species invasion in a lake, they have a wide array of potential ecological applications.
Stable isotope analysis provides a powerful tool to identify the energy sources which fuel consumers, to understand trophic interactions and to infer consumer trophic position (TP), an important ...concept that describes the ecological role of consumers in food webs. However, current methods for estimating TP using stable isotopes are limited and do not fulfil the complete potential of the isotopic approach. For instance, researchers typically use point estimates for key parameters including trophic discrimination factors and isotopic baselines, and do not explicitly include variance associated with these parameters when calculating TP.
We present “tRophicPosition,” an r package incorporating a Bayesian model for the calculation of consumer TP at the population level using stable isotopes, with one or two baselines. It combines Markov Chain Monte Carlo simulations through JAGS and statistical and graphical analyses using R. We model consumer and baseline observations using relevant statistical distributions, allowing them to be treated as random variables. The calculation of TP—a random parameter—for one baseline follows standard equations linking 15N enrichment per trophic level and the trophic position of the baseline (e.g. a primary producer or primary consumer). In the case of two baselines, a simple mixing model incorporating δ13C allows for the differentiation between two distinct sources of nitrogen, thus including heterogeneity derived from alternatives sources of δ15N.
Methods currently implemented in “tRophicPosition” include loading, plotting and summarizing stable isotope data either from multiple sites and/or communities or a local assemblage; loading trophic discrimination factors from an internal database or generating them; defining and initializing a Bayesian model of TP; sampling posterior parameters; analysing, comparing and plotting posterior estimates of TP and other parameters; and calculating a parametric (non‐Bayesian) TP estimate. Additionally, full documentation including examples, multiple vignettes and code are available for download.
Foreign Language Resumen
El análisis de isótopos estables es una poderosa herramienta para identificar qué vías energéticas alimentan a los consumidores, para entender las interacciones tróficas, y también para inferir la posición trófica (PT) de los consumidores, un concepto importante que describe el rol ecológico de los consumidores en las tramas tróficas. Sin embargo, los métodos actuales para estimar la PT utilizando isótopos estables están limitados y no permiten alcanzar el potencial de la aproximación isotópica. Por ejemplo, los investigadores típicamente utilizan estimaciones puntuales de parámetros claves incluyendo factores de discriminación trófica y líneas base isotópicas, y no incorporan explícitamente la varianza asociada con estos parámetros cuando calculan la PT.
Presentamos “tRophicPosition,” un paquete de R para isótopos estables que incorpora un modelo Bayesiano para el cálculo de la PT en consumidores al nivel ecológico de población, con una o dos líneas base. Este paquete combina simulaciones de cadenas de Markov Monte Carlo a través de JAGS y utilizando los análisis estadísticos y gráficos de R. Modelamos las observaciones de consumidores y líneas base utilizando distribuciones estadísticas relevantes, por lo que son tratadas como variables aleatorias. El cálculo de la PT—un parámetro aleatorio—para una línea base considera ecuaciones estándar que vinculan el enriquecimiento en 15N por nivel trófico y el nivel trófico de la línea base (p.e. un productor primario o un consumidor primario). En el caso de dos líneas base, un modelo de mezcla simple incorporando δ13C permite la diferenciación entre dos fuentes distintas de nitrógeno, incluyendo de esta forma la heterogeneidad derivada de fuentes alternativas de δ15N.
Los métodos actualmente implementados en “tRophicPosition” incluyen cargar, graficar y resumir datos de isótopos estables desde múltiples sitios y/o comunidades o ensambles locales; cargar factores de discriminación trófica desde una base de datos interna o generarlos; definir e inicializar un modelo Bayesiano para la PT; muestrear parámetros a posteriori; analizar, comparar y graficar estimaciones a posteriori de la TP y otros parámetros; y calcular una estimación frecuentista (no Bayesiana) para la PT. Adicionalmente, toda la documentación incluyendo ejemplos, distintas viñetas y el código están disponibles para descarga.
Stable isotope mixing models are increasingly used to quantify consumer diets, but may be misused and misinterpreted. We address major challenges to their effective application. Mixing models have ...increased rapidly in sophistication. Current models estimate probability distributions of source contributions, have user-friendly interfaces, and incorporate complexities such as variability in isotope signatures, discrimination factors, hierarchical variance structure, covariates, and concentration dependence. For proper implementation of mixing models, we offer the following suggestions. First, mixing models can only be as good as the study and data. Studies should have clear questions, be informed by knowledge of the system, and have strong sampling designs to effectively characterize isotope variability of consumers and resources on proper spatio-temporal scales. Second, studies should use models appropriate for the question and recognize their assumptions and limitations. Decisions about source grouping or incorporation of concentration dependence can influence results. Third, studies should be careful about interpretation of model outputs. Mixing models generally estimate proportions of assimilated resources with substantial uncertainty distributions. Last, common sense, such as graphing data before analyzing, is essential to maximize usefulness of these tools. We hope these suggestions for effective implementation of stable isotope mixing models will aid continued development and application of this field.
...research translation is needed. ...powerful leadership must continue and must include articulate advocacy for the im- portance of health in building and redevelopment decisions.
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